REGRESSION ANALYSIS
USING BOWLING PIN FACTORY(FACTISM)
IME 435/L
DESIGN OF EXPERIMENT
YOUNG KIM
2/25/2014
IME
DEPARTMENT
CALIFORNIA
STATE POLYTECHNIC UNIVERSITY
Title:
Simple regression analysis using bowling pin factory (FACTISM)
Simple regression analysis using bowling pin factory (FACTISM)
Statement
of the problem:
How change in pressure in 8 different levels will affect response, weight, will be investigated by performing simple regression analysis. Some of questions to be answered at the end of the experiment are:
How change in pressure in 8 different levels will affect response, weight, will be investigated by performing simple regression analysis. Some of questions to be answered at the end of the experiment are:
a. If the
chosen factor is correlated with the response variable (launch distance) or
not.
b. Is the
correlation positive or negative?
c. Is the
correlation strong or weak?
d. What is the
correlation coefficient? What is its significance?
e. What is the
coefficient of determination? What is its significance?
Materials
or Tools:
FACTISM
Microsoft Excel
Microsoft Words
FACTISM
Microsoft Excel
Microsoft Words
Assumptions:
1. Coefficient of correlation with value of less than 0.85 is considered to be insignificant.
2. Coefficient of determination with value of less than 0.723 is considered to be insignificant.
1. Coefficient of correlation with value of less than 0.85 is considered to be insignificant.
2. Coefficient of determination with value of less than 0.723 is considered to be insignificant.
Procedure:
1. Collect responses from Factism by changing pressure value to 80, 81, 82, 83, 84, 85, and 86 with 6 replications for each level.
2. Perform simple linear regression analysis manually and using excel.
1. Collect responses from Factism by changing pressure value to 80, 81, 82, 83, 84, 85, and 86 with 6 replications for each level.
2. Perform simple linear regression analysis manually and using excel.
Results:
Using manual method:
Using manual method:
Findings &
conclusion:
a. If the
chosen factor is correlated with the response variable (launch distance) or
not.
- From the regression analysis we can see that there is no correlation between the pressure and weight. This is supported by the fact that our slope or b_1 is relatively small. Yet, slope by itself does not tell us the strength of the correlation.
- From the regression analysis we can see that there is no correlation between the pressure and weight. This is supported by the fact that our slope or b_1 is relatively small. Yet, slope by itself does not tell us the strength of the correlation.
b. Is the correlation
positive or negative?
-Since our slope is positive, the relationship is positive relationship.
-Since our slope is positive, the relationship is positive relationship.
c. Is the
correlation strong or weak?
-This correlation is said to be very weak due to its small value in coefficient of correlation.
-This correlation is said to be very weak due to its small value in coefficient of correlation.
d. What is the
correlation coefficient? What is its significance?
-The correlation coefficient in this particular analysis is 0.069144. From our assumption, we have decided that R value with less than 0.85 is to be insignificant. Hence, it is confident to conclude that pressure does not have any effect on weight.
-The correlation coefficient in this particular analysis is 0.069144. From our assumption, we have decided that R value with less than 0.85 is to be insignificant. Hence, it is confident to conclude that pressure does not have any effect on weight.
e. What is the
coefficient of determination? What is its significance?
-The coefficient of determination in this particular analysis is calculated to be 0.004781 by which mean, any variation in weight is caused by pressure only .5% of the time.
-The coefficient of determination in this particular analysis is calculated to be 0.004781 by which mean, any variation in weight is caused by pressure only .5% of the time.
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